nn_layers.py 文件源码

def output_func(self, input):
        q = input[0]
        all_list = [q]
        for i in xrange(self.position):
            dot = T.batched_dot(q, T.dot(input[i + 1], self.W[i].T))
            all_list.append(dot.dimshuffle(0, 'x'))
            all_list.append(input[i + 1])
        begin_index = self.position
        for i in range(1, self.position):
            for j in range(0, i):
                dot = T.batched_dot(input[j + 1], T.dot(input[i + 1], self.W[begin_index].T))
                all_list.append(dot.dimshuffle(0, 'x'))
                #begin_index += 1
        out = T.concatenate(all_list, axis=1)

        # dot = T.batched_dot(q, T.batched_dot(a, self.W))
        #dot = T.batched_dot(q, T.dot(a, self.W.T))
        #out = T.concatenate([dot.dimshuffle(0, 'x'), q, a], axis=1)
        return out